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Jobgether

Lead GenAI SaaS / Platform Engineer

IndiaRemote · India
Staff · Full-time · Security & IT
POSTED 9 NOVVERIFIED 1H AGO
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Role
1 days opentrue age
Posted 9 Nov
Pay
$82k–$114kno pay posted
Market p25–p75
₹20.3L–₹82.3L
Jobgether p25–p75
$82k–$114kn=3
India · n=8 · 365d to 6 Nov
CompanyJobgether →
2,000open roles
Opened · 30d
+2,605
Closed · 30d
−2,667
8d of snapshots · 30d window
Market
1,322open · Staff Backend
Opened · 7d
+937% of open
All backend
8,379open
All tracked boards · live 10 Nov · n=1,322
PythonAWSAzureLLMs

Accountabilities

  • GenAI Platform Administration: Own the end-to-end administration, configuration, governance, and lifecycle management of enterprise generative AI platforms, including ChatGPT Enterprise, Claude, and other internal AI solutions.
  • Platform Architecture & Scalability: Design and maintain scalable SaaS architectures that support enterprise-wide AI adoption, ensuring platform reliability, performance, and operational efficiency.
  • Integrations & Extensibility: Develop and implement Model Context Protocol (MCP) connectors, REST API integrations, and secure data pipelines to connect LLM platforms with enterprise applications, systems, and business tools.
  • Identity & Access Management: Establish and maintain enterprise-grade authentication and authorization frameworks using SAML 2.0, SCIM provisioning, OAuth, and role-based access control (RBAC), leveraging Okta and Microsoft Entra ID.
  • Security & AI Governance: Define and enforce security policies, data privacy controls, compliance requirements, and responsible AI usage guidelines to ensure secure and controlled adoption of generative AI technologies.
  • Automation & Scripting: Develop automation scripts and operational workflows using Python or PowerShell to streamline user provisioning, platform configuration, usage monitoring, and policy enforcement.
  • Platform Monitoring & Reliability: Monitor platform health, availability, performance, and usage across enterprise environments, identifying operational risks and implementing preventive improvements.
  • Incident & Escalation Management: Lead complex technical troubleshooting and Tier 3 incident escalations, ensuring timely resolution and minimizing service disruptions.
  • Consumption & License Management: Monitor AI platform consumption, licensing metrics, user activity, and operational costs to optimize resource utilization and platform efficiency.
  • Cloud Infrastructure Operations: Support reliable platform operations across AWS and Azure environments, ensuring appropriate logging, monitoring, security, and infrastructure integration.
  • Cross-Functional Collaboration: Partner with Security, Workplace IT, endpoint engineering, and MDM teams to coordinate platform requirements and align SaaS architecture with enterprise technology standards.
  • Continuous Improvement: Stay informed about emerging LLM technologies, AI integration standards, and SaaS engineering practices to continuously improve enterprise AI capabilities.

Requirements

  • 8–12 years of professional experience in Enterprise SaaS Engineering, Cloud Infrastructure, Platform Engineering, or Enterprise Platform Administration.
  • Strong hands-on experience designing, implementing, and managing enterprise SaaS platforms and complex technical environments.
  • Identity & Access Management: Deep understanding of modern IAM architectures, including Okta, Microsoft Entra ID, Single Sign-On (SSO), SAML 2.0, SCIM provisioning, OAuth flows, and role-based access control (RBAC).
  • Generative AI & LLM Platforms: Practical familiarity with enterprise generative AI platforms, LLM toolchains, AI integrations, and enterprise AI governance frameworks.
  • Experience administering ChatGPT Enterprise, Claude Enterprise, or comparable enterprise AI platforms is a significant advantage.
  • Knowledge of emerging AI integration standards, particularly Model Context Protocol (MCP), and their application in enterprise environments.
  • Programming & Automation: Strong proficiency in Python or PowerShell, with demonstrated experience building automation scripts and managing operational workflows.
  • API Integration: Hands-on experience with REST APIs, API authentication, system integrations, and secure data exchange between enterprise applications.
  • Cloud Technologies: Solid understanding of AWS or Microsoft Azure, including cloud infrastructure, enterprise services, and platform operations.
  • Monitoring & Incident Management: Experience with enterprise logging, monitoring, platform health management, troubleshooting, and complex incident resolution.
  • Security & Compliance: Strong understanding of enterprise security principles, data privacy, access governance, and least-privilege security models.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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Source · JobgetherFirst seen 9 NovOriginal ↗